plotHmmStates              package:aCGH              R Documentation

_P_l_o_t_t_i_n_g _t_h_e _e_s_t_i_m_a_t_e_d _h_m_m _s_t_a_t_e_s _a_n_d _l_o_g_2 _r_a_t_i_o_s _f_o_r _e_a_c_h _s_a_m_p_l_e.

_D_e_s_c_r_i_p_t_i_o_n:

     This function displays the estimated hmm states and log2 ratios
     for each sample.

_U_s_a_g_e:

     plotHmmStates(aCGH.obj, sample.ind, chr = 1:num.chromosomes(aCGH.obj),
                  statesres = hmm.merged(aCGH.obj), maxChrom = 23,
                  chrominfo = human.chrom.info.Jul03, yScale = c(-2, 2),
                  samplenames = sample.names(aCGH.obj))

_A_r_g_u_m_e_n_t_s:

aCGH.obj: object of class aCGH

sample.ind: index of the sample to be plotted relative to the data
          matrix (i.e. column index in the file)

statesres: matrix containing states informations. defaults to the
          states selected using the first  model selection criterionof
          'aCGH.obj'

     chr: vector of chromosomes to be plotted

  yScale: specified scale for Y-exis

maxChrom: highest chromosome to show

chrominfo: a chromosomal information associated with the mapping of the
          data

samplenames: vector of sample names

_D_e_t_a_i_l_s:

     Each chromosome is plotted on a separate  page and contains two
     figures. The top figure shows the observed log2ratios and the
     bottom figure shows predicted values for all clones but outliers
     which show observed values. The genomic events are indicated on
     both figures as following. The first clone after transition is
     indicated with solid blue line and the last clone after
     transitions is shown with dotted green line. Focal aberrations
     clones are colored orange, amplifications are colored red and
     outliers are yellow.

_A_u_t_h_o_r(_s):

     Jane Fridlyand

_R_e_f_e_r_e_n_c_e_s:

     Application of Hidden Markov Models to the analysis of the array
     CGH data, Fridlyand et.al., _JMVA_, 2004

_S_e_e _A_l_s_o:

     'aCGH' 'find.hmm.states' 'plotGenome'

_E_x_a_m_p_l_e_s:

     data(colorectal)
     plotHmmStates(colorectal, 1)

